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Wednesday, 11 May 2016

Follow Up: Providing A Better Definition Of “Objectivity”. Hempel’s Ravens And The Paradox Of Confirmation.

In the last
blog post, the term “objectivity” was regularly used, however, the definition of
this term was not as clearly defined as it could have been. In this post I will
attempt to explain how one can still be justified in saying that something is “objective”,
while at the same time acknowledging the problems with the term “objective”.

When the
term “objective” is used, often times it is referring to something that is
believed to be ontologically true. However, in science and other areas of life
it is essential to analyse what we mean when we say that something is true
scientifically. Evidence for whether a statement
is considered to be objective or not, depends on evidence for that statement.

In the
philosophy of science, the ravens paradox (Hempel’s Ravens) is worth analysing.
Consider the proposition that “all ravens are black”. This can be understood to
be an objective fact because to date no one has observed anything that is a
none black raven. When this is the case, does observing anything that is not black
and not a raven become evidence for the proposition that “all ravens are black”?
At the moment I am writing this blog post on a grey laptop, does the fact that
my laptop is not black and not a raven, count as evidence for the proposition
that “all ravens are black”?

The paradox
reveals problems with evaluating evidence in cognitive science. In psychology,
if P happens to be greater than 0.5 on a variety of different occasions, one
might think that after a series of studies reveal that P>.05 this confirms
that the hypothesis is ontologically true. This approach is not unproblematic,
because it could very well be the case that certain research methodologies
contradict one another. Alternatively there may be flaws with the individual
studies or even the set P value. Also journals are less likely to publish
articles based on experiments with a null hypothesis, so publicly it may appear
as if a series of tests confirm a certain hypothesis when the reverse could be true.

Hopefully
by analysing solutions to the raven paradox we can arrive at a better definition
of what we mean we say that something is objectively true or scientifically
true.

Hempel’s
solution is to make a similar comparison to the proposition: “all sodium salts
burn yellow”. If one holds a piece of ice to fire instead of salt and it fails
to burn yellow, does this confirm hypothesis? According to Hempel, this can
only count as evidence in favour for the first proposition if one avoids any
reference to previous knowledge. If one thinks about the solution to the raven
paradox as a scientific hypothesis, can we be justified in saying that a
proposition is ontologically true if we don’t have prior knowledge?

Maher
sought to accept the conclusion of the paradox but refine it. A non-raven
confirms that “all ravens are black” because the fact that the object is not a
raven removes the possibility that the object is a counter example to the
generalisation. It also reduces the probability that unobserved objects are
ravens.

The Bayesian-Carnap
solution states that it’s not the case that observing anything that is
non-black and non-raven enforces the hypothesis, but instead that the
prevalence of black ravens means that “all ravens are blacks”. This proposition
is also slightly modified because it would consider the existence of something
that is non-black and non-raven (such as a grey laptop) to be part of the same
proposition as “all ravens are black”. Thus, it helps to reaffirm the
proposition that all ravens in existence are black.

The role of background knowledge was mentioned in the
Carnap solution, another problem with why a scientific truth can not necessarily
be said to be ontologically true is because

scientific theories inevitably rely on knowledge from
previous theories. It is also impossible to test a scientific theory in it’s
entirely (see Duhem-Quine Thesis). Also one cannot have all of the
background knowledge regarding a theory, so theories are susceptible to change
and modification based on new information.

If anything
is to be referred to as being “objectively true”, one should not infer that
this is the same as saying that something is ontologically true. Saying that
something is “objective” should be understood as saying something is believed to be true based on the
existing data. Perhaps this approach is more instrumentalist or anti-realist,
but when we can’t be sure if something is ontologically true it only makes
sense to embrace this definition of “objectivity”.